1. Field of the Invention
The present invention relates to providing efficient enforced resource consumption rate limits. In particular, it relates to determining when to recalculate resource availability.
2. Description of the Related Art
The task of modern network administration differs significantly from that of days gone by. Not just a decade ago, network administration primarily entailed the addition and deletion of network users, the management of print queues, and the supervision and operation of daily backup procedures. Most if not all resources required by network applications remained present in the network itself, and few if any network applications depended upon the operation of other, co-executing applications.
Much has changed since the early days of network computing. Today, enterprise computing permeates the electronic landscape. While some enterprise applications remain largely stand-alone, most rely in some respect on a co-existing enterprise application or a soft enterprise resource, such as a database application, web application server, or other cooperating component. Thus, the administration of the network has advanced far beyond user and print queue administration and daily backup routines. Today, the inter-dependencies among network components present a significant challenge to the network administrator. In this regard, the management of a single network component can depend upon the state of a multiplicity of other network components.
Changing components or configuration settings with a network architecture requires careful consideration of the potential impact of a given change. System changes generally are known to be the source of architectural missteps in even the simplest of network structures. Further, as system complexity increases, the number of errors caused by a configuration change increases exponentially. Thus, system unavailability in a complex computing network is typically caused by an incorrectly applied configuration change.
The most useful and relevant history of past configuration changes is usually not easily accessible to an individual making a configuration change. Although the relevant data may be available, finding the data is heavily reliant on the specifics of the current configuration and the configuration change desired. Browsing or searching through the available configuration change data can be time consuming and tedious for the user. Additionally, available configuration change data can sometimes be faulty or comply incorrect. Thus, there is currently no easy way to find the best and most relevant advice regarding configuration changes on a complex computing network. For this reason, configuration changes are often made blindly with regard to the prior experience of others making configuration changes.
Therefore, there is a need for improvements over the prior art, and more particularly, there is a need for a more efficient way of effectuating a change to a configuration in a complex computing network.